SlideShare a Scribd company logo
1 of 10
Download to read offline
Generating Various and Consistent Behaviors
      in Simulations
      Benoît Lacroix 1,2, Philippe Mathieu 2 and Andras Kemeny 1




1   Renault, Technical Center for Simulation
2   LIFL, University of Lille                  March 26, 2009   PAAMS 2009
Context and motivation

      Renault / LIFL UMR CNRS collaboration
      Context: traffic simulation in driving simulators
          Evaluation of ergonomics, embedded systems, design…
      Needs
          Various and consistent behaviors for autonomous vehicles (cautious, aggressive…)
          Usable by scenario designers

      Idea
          Driving psychologists classify drivers depending on their behavior (Saad, 1992)
          Drivers use set of norms (based on Highway Code, informal rules…)
          But they do not strictly follow these norms

      Generic approach to address the issue
          Behaviors description using norms
          Generation engine managing the determinism
          Monitoring



Benoit Lacroix
Renault, Technical Center for Simulation   March 26, 2009   PAAMS 2009             2
Normative description of behaviors

      Normative systems (Noriega, 1997; Esteva et al., 2001; Vazquez-Salceda et al., 2005)
          Organizational control in multi-agent based simulations
          Improve agents coordination, communication…

      In our case
          Institution: parameters and associated definition domains
          Norms: subsets of these parameters and domains
          Behaviors: instantiations of these norms

      For instance, in traffic
             Parameters: maximal speed, safety time…
             Institution: bounds of these parameters (max speed in [0,300] km/h)
             Norms: cautious, aggressive drivers (max speed in [140,160] km/h)
             Behavior: a cautious, an aggressive (max speed = 156 km/h)




Benoit Lacroix
Renault, Technical Center for Simulation   March 26, 2009      PAAMS 2009                 3
Generation engine

        Variety
               Randomly select parameters
                from a norm
                      Behavioral variety within a
                       norm
                      Allow violations: one or more
                       parameters outside the limits


 Consistency
          Guaranteed when generation within norms limits
          Mechanism to reject aberrant behaviors (quantification)
          Reaction to violations at runtime


Benoit Lacroix
Renault, Technical Center for Simulation   March 26, 2009   PAAMS 2009   4
Monitoring

 Emergence of new norms
          Feedback to the users
          Improve design and calibration

 Calibration with real data
          Learning norms from real data sets

 Unsupervised learning
          Kohonen Neural Networks
          Description of the data space
          Linear component analysis


Benoit Lacroix
Renault, Technical Center for Simulation   March 26, 2009   PAAMS 2009   5
Application

 Application
          Driving simulation software SCANeR™ II
          Ergonomics, embedded systems, design, headlights…

 Description
          Agents’ decision model: perception – decision (finite state automata) –
           action (vehicle dynamic model)
          Institution parameters = existing vehicles parameters of traffic model
          Traffic managed by the existing model

 Uses
          Introduction of driving styles
          Generation of the “ambient” traffic




Benoit Lacroix
Renault, Technical Center for Simulation   March 26, 2009   PAAMS 2009    6
Benoit Lacroix
Renault, Technical Center for Simulation   March 26, 2009   PAAMS 2009   7
Experimental results

 Highway database
          11 km, 3000 veh/h
          Normal, aggressive and
           cautious drivers


 Speed distributions
          More norms increase variety
          Increased dynamicity


 Lane repartition
          Aggressive on left lane
          Cautious on right lane


Benoit Lacroix
Renault, Technical Center for Simulation   March 26, 2009   PAAMS 2009   8
Conclusion

 Easily create various behaviors
 Manage the generation process
          Guaranty the consistency of the behaviors
          Allow violations if wished
 Wide application range
 Non-intrusive

 Perspectives
          Norms calibration with real data



Benoit Lacroix
Renault, Technical Center for Simulation   March 26, 2009   PAAMS 2009   9
Thank you for your attention




                                           Contact: benoit.lacroix@gmail.com




Benoit Lacroix
Renault, Technical Center for Simulation   March 26, 2009         PAAMS 2009   10

More Related Content

Viewers also liked

Quand commencer la révision avant la rentrée scolaire
Quand commencer la révision avant la rentrée scolaireQuand commencer la révision avant la rentrée scolaire
Quand commencer la révision avant la rentrée scolaireEducationcm
 
Webinaire enseignants Etablir les profils d'apprentissage de mes parents
Webinaire enseignants Etablir les profils d'apprentissage de mes parentsWebinaire enseignants Etablir les profils d'apprentissage de mes parents
Webinaire enseignants Etablir les profils d'apprentissage de mes parentsEducationcm
 
Construction Safety Talks - 01
Construction Safety Talks - 01Construction Safety Talks - 01
Construction Safety Talks - 01John Keller
 
webinaire parents Quelles activites parascolaires pour l'annee
webinaire parents Quelles activites parascolaires pour l'anneewebinaire parents Quelles activites parascolaires pour l'annee
webinaire parents Quelles activites parascolaires pour l'anneeEducationcm
 
Empowering Communiites through Policy Development-The PMB Model
Empowering Communiites through Policy Development-The PMB ModelEmpowering Communiites through Policy Development-The PMB Model
Empowering Communiites through Policy Development-The PMB ModelSulleiman Adediran
 
Workers Comp Benchmarking Analysis
Workers Comp Benchmarking AnalysisWorkers Comp Benchmarking Analysis
Workers Comp Benchmarking AnalysisJohn Keller
 
Data integration with embulk
Data integration with embulkData integration with embulk
Data integration with embulkTeguh Nugraha
 
Webinaire enseignants structurer 1h cours
Webinaire enseignants structurer 1h coursWebinaire enseignants structurer 1h cours
Webinaire enseignants structurer 1h coursEducationcm
 

Viewers also liked (9)

Quand commencer la révision avant la rentrée scolaire
Quand commencer la révision avant la rentrée scolaireQuand commencer la révision avant la rentrée scolaire
Quand commencer la révision avant la rentrée scolaire
 
Webinaire enseignants Etablir les profils d'apprentissage de mes parents
Webinaire enseignants Etablir les profils d'apprentissage de mes parentsWebinaire enseignants Etablir les profils d'apprentissage de mes parents
Webinaire enseignants Etablir les profils d'apprentissage de mes parents
 
Construction Safety Talks - 01
Construction Safety Talks - 01Construction Safety Talks - 01
Construction Safety Talks - 01
 
Cst32
Cst32Cst32
Cst32
 
webinaire parents Quelles activites parascolaires pour l'annee
webinaire parents Quelles activites parascolaires pour l'anneewebinaire parents Quelles activites parascolaires pour l'annee
webinaire parents Quelles activites parascolaires pour l'annee
 
Empowering Communiites through Policy Development-The PMB Model
Empowering Communiites through Policy Development-The PMB ModelEmpowering Communiites through Policy Development-The PMB Model
Empowering Communiites through Policy Development-The PMB Model
 
Workers Comp Benchmarking Analysis
Workers Comp Benchmarking AnalysisWorkers Comp Benchmarking Analysis
Workers Comp Benchmarking Analysis
 
Data integration with embulk
Data integration with embulkData integration with embulk
Data integration with embulk
 
Webinaire enseignants structurer 1h cours
Webinaire enseignants structurer 1h coursWebinaire enseignants structurer 1h cours
Webinaire enseignants structurer 1h cours
 

Similar to Generating Various and Consistent Behaviors in Simulations

Automated generation of various and consistent populations in multi-agent sim...
Automated generation of various and consistent populations in multi-agent sim...Automated generation of various and consistent populations in multi-agent sim...
Automated generation of various and consistent populations in multi-agent sim...Benoit Lacroix
 
Rich Internet Application Testing Using Execution Trace Data
Rich Internet Application Testing  Using Execution Trace Data Rich Internet Application Testing  Using Execution Trace Data
Rich Internet Application Testing Using Execution Trace Data Porfirio Tramontana
 
Automated Testing of Autonomous Driving Assistance Systems
Automated Testing of Autonomous Driving Assistance SystemsAutomated Testing of Autonomous Driving Assistance Systems
Automated Testing of Autonomous Driving Assistance SystemsLionel Briand
 
TRAFFIC SIGN BOARD RECOGNITION AND VOICE ALERT SYSTEM USING CNN
TRAFFIC SIGN BOARD RECOGNITION AND VOICE ALERT SYSTEM USING CNNTRAFFIC SIGN BOARD RECOGNITION AND VOICE ALERT SYSTEM USING CNN
TRAFFIC SIGN BOARD RECOGNITION AND VOICE ALERT SYSTEM USING CNNIRJET Journal
 
Obstacle Detection and Collision Avoidance System
Obstacle Detection and Collision Avoidance SystemObstacle Detection and Collision Avoidance System
Obstacle Detection and Collision Avoidance SystemIRJET Journal
 
verification of autonomous robotic system
verification of autonomous robotic systemverification of autonomous robotic system
verification of autonomous robotic systemASJAYASURYA
 
VANET Simulation - Jamal Toutouh
VANET Simulation - Jamal  ToutouhVANET Simulation - Jamal  Toutouh
VANET Simulation - Jamal ToutouhJamal Toutouh, PhD
 
PreMonR - A Reactive Platform To Monitor Reactive Application
PreMonR - A Reactive Platform To Monitor Reactive ApplicationPreMonR - A Reactive Platform To Monitor Reactive Application
PreMonR - A Reactive Platform To Monitor Reactive ApplicationKnoldus Inc.
 
K-10714 ABHISHEK(AUTOMOBILE SURVEILLANCE)
K-10714 ABHISHEK(AUTOMOBILE SURVEILLANCE)K-10714 ABHISHEK(AUTOMOBILE SURVEILLANCE)
K-10714 ABHISHEK(AUTOMOBILE SURVEILLANCE)shailesh yadav
 
Traffic Sign Recognition using CNNs
Traffic Sign Recognition using CNNsTraffic Sign Recognition using CNNs
Traffic Sign Recognition using CNNsIRJET Journal
 
Traffic Management system using Deep Learning
Traffic Management system using Deep LearningTraffic Management system using Deep Learning
Traffic Management system using Deep LearningIRJET Journal
 
Natural Computing for Vehicular Networks
Natural Computing for Vehicular NetworksNatural Computing for Vehicular Networks
Natural Computing for Vehicular NetworksJamal Toutouh, PhD
 
Traffic Signboard Classification with Voice alert to the driver.pptx
Traffic Signboard Classification with Voice alert to the driver.pptxTraffic Signboard Classification with Voice alert to the driver.pptx
Traffic Signboard Classification with Voice alert to the driver.pptxharimaxwell0712
 
FactIS Wayside CM Systems
FactIS Wayside CM SystemsFactIS Wayside CM Systems
FactIS Wayside CM SystemsMonicaLynxrail
 
Traffic Light Control
Traffic Light ControlTraffic Light Control
Traffic Light Controlhoadktd
 
Simulation of traffic engg.
Simulation of traffic engg.Simulation of traffic engg.
Simulation of traffic engg.vijay reddy
 
Deep Learning Approach Model for Vehicle Classification using Artificial Neur...
Deep Learning Approach Model for Vehicle Classification using Artificial Neur...Deep Learning Approach Model for Vehicle Classification using Artificial Neur...
Deep Learning Approach Model for Vehicle Classification using Artificial Neur...IRJET Journal
 
"How to Test and Validate an Automated Driving System," a Presentation from M...
"How to Test and Validate an Automated Driving System," a Presentation from M..."How to Test and Validate an Automated Driving System," a Presentation from M...
"How to Test and Validate an Automated Driving System," a Presentation from M...Edge AI and Vision Alliance
 

Similar to Generating Various and Consistent Behaviors in Simulations (20)

Automated generation of various and consistent populations in multi-agent sim...
Automated generation of various and consistent populations in multi-agent sim...Automated generation of various and consistent populations in multi-agent sim...
Automated generation of various and consistent populations in multi-agent sim...
 
Rich Internet Application Testing Using Execution Trace Data
Rich Internet Application Testing  Using Execution Trace Data Rich Internet Application Testing  Using Execution Trace Data
Rich Internet Application Testing Using Execution Trace Data
 
Automated Testing of Autonomous Driving Assistance Systems
Automated Testing of Autonomous Driving Assistance SystemsAutomated Testing of Autonomous Driving Assistance Systems
Automated Testing of Autonomous Driving Assistance Systems
 
TRAFFIC SIGN BOARD RECOGNITION AND VOICE ALERT SYSTEM USING CNN
TRAFFIC SIGN BOARD RECOGNITION AND VOICE ALERT SYSTEM USING CNNTRAFFIC SIGN BOARD RECOGNITION AND VOICE ALERT SYSTEM USING CNN
TRAFFIC SIGN BOARD RECOGNITION AND VOICE ALERT SYSTEM USING CNN
 
Obstacle Detection and Collision Avoidance System
Obstacle Detection and Collision Avoidance SystemObstacle Detection and Collision Avoidance System
Obstacle Detection and Collision Avoidance System
 
verification of autonomous robotic system
verification of autonomous robotic systemverification of autonomous robotic system
verification of autonomous robotic system
 
VANET Simulation - Jamal Toutouh
VANET Simulation - Jamal  ToutouhVANET Simulation - Jamal  Toutouh
VANET Simulation - Jamal Toutouh
 
PreMonR - A Reactive Platform To Monitor Reactive Application
PreMonR - A Reactive Platform To Monitor Reactive ApplicationPreMonR - A Reactive Platform To Monitor Reactive Application
PreMonR - A Reactive Platform To Monitor Reactive Application
 
K-10714 ABHISHEK(AUTOMOBILE SURVEILLANCE)
K-10714 ABHISHEK(AUTOMOBILE SURVEILLANCE)K-10714 ABHISHEK(AUTOMOBILE SURVEILLANCE)
K-10714 ABHISHEK(AUTOMOBILE SURVEILLANCE)
 
Traffic Sign Recognition using CNNs
Traffic Sign Recognition using CNNsTraffic Sign Recognition using CNNs
Traffic Sign Recognition using CNNs
 
Traffic Management system using Deep Learning
Traffic Management system using Deep LearningTraffic Management system using Deep Learning
Traffic Management system using Deep Learning
 
Natural Computing for Vehicular Networks
Natural Computing for Vehicular NetworksNatural Computing for Vehicular Networks
Natural Computing for Vehicular Networks
 
Presentation ATM
Presentation ATMPresentation ATM
Presentation ATM
 
Traffic Signboard Classification with Voice alert to the driver.pptx
Traffic Signboard Classification with Voice alert to the driver.pptxTraffic Signboard Classification with Voice alert to the driver.pptx
Traffic Signboard Classification with Voice alert to the driver.pptx
 
FactIS Wayside CM Systems
FactIS Wayside CM SystemsFactIS Wayside CM Systems
FactIS Wayside CM Systems
 
Traffic Light Control
Traffic Light ControlTraffic Light Control
Traffic Light Control
 
Simulation of traffic engg.
Simulation of traffic engg.Simulation of traffic engg.
Simulation of traffic engg.
 
PROSPECT - PROactive Safety for PEdestrians and CyclisTs
PROSPECT - PROactive Safety for PEdestrians and CyclisTsPROSPECT - PROactive Safety for PEdestrians and CyclisTs
PROSPECT - PROactive Safety for PEdestrians and CyclisTs
 
Deep Learning Approach Model for Vehicle Classification using Artificial Neur...
Deep Learning Approach Model for Vehicle Classification using Artificial Neur...Deep Learning Approach Model for Vehicle Classification using Artificial Neur...
Deep Learning Approach Model for Vehicle Classification using Artificial Neur...
 
"How to Test and Validate an Automated Driving System," a Presentation from M...
"How to Test and Validate an Automated Driving System," a Presentation from M..."How to Test and Validate an Automated Driving System," a Presentation from M...
"How to Test and Validate an Automated Driving System," a Presentation from M...
 

Recently uploaded

Unblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesUnblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesSinan KOZAK
 
Benefits Of Flutter Compared To Other Frameworks
Benefits Of Flutter Compared To Other FrameworksBenefits Of Flutter Compared To Other Frameworks
Benefits Of Flutter Compared To Other FrameworksSoftradix Technologies
 
My Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationMy Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationRidwan Fadjar
 
AI as an Interface for Commercial Buildings
AI as an Interface for Commercial BuildingsAI as an Interface for Commercial Buildings
AI as an Interface for Commercial BuildingsMemoori
 
Making_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptx
Making_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptxMaking_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptx
Making_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptxnull - The Open Security Community
 
"LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks...
"LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks..."LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks...
"LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks...Fwdays
 
costume and set research powerpoint presentation
costume and set research powerpoint presentationcostume and set research powerpoint presentation
costume and set research powerpoint presentationphoebematthew05
 
Human Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsHuman Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsMark Billinghurst
 
New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024
New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024
New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024BookNet Canada
 
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024BookNet Canada
 
Pigging Solutions Piggable Sweeping Elbows
Pigging Solutions Piggable Sweeping ElbowsPigging Solutions Piggable Sweeping Elbows
Pigging Solutions Piggable Sweeping ElbowsPigging Solutions
 
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticsKotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticscarlostorres15106
 
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticsKotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticsAndrey Dotsenko
 
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Alan Dix
 
Transcript: New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024Transcript: New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024BookNet Canada
 
Install Stable Diffusion in windows machine
Install Stable Diffusion in windows machineInstall Stable Diffusion in windows machine
Install Stable Diffusion in windows machinePadma Pradeep
 
Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024Enterprise Knowledge
 
Scanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsScanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsRizwan Syed
 
Unleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding ClubUnleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding ClubKalema Edgar
 

Recently uploaded (20)

Unblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesUnblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen Frames
 
E-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptx
E-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptxE-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptx
E-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptx
 
Benefits Of Flutter Compared To Other Frameworks
Benefits Of Flutter Compared To Other FrameworksBenefits Of Flutter Compared To Other Frameworks
Benefits Of Flutter Compared To Other Frameworks
 
My Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationMy Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 Presentation
 
AI as an Interface for Commercial Buildings
AI as an Interface for Commercial BuildingsAI as an Interface for Commercial Buildings
AI as an Interface for Commercial Buildings
 
Making_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptx
Making_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptxMaking_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptx
Making_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptx
 
"LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks...
"LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks..."LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks...
"LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks...
 
costume and set research powerpoint presentation
costume and set research powerpoint presentationcostume and set research powerpoint presentation
costume and set research powerpoint presentation
 
Human Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsHuman Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR Systems
 
New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024
New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024
New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024
 
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
 
Pigging Solutions Piggable Sweeping Elbows
Pigging Solutions Piggable Sweeping ElbowsPigging Solutions Piggable Sweeping Elbows
Pigging Solutions Piggable Sweeping Elbows
 
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticsKotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
 
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticsKotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
 
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
 
Transcript: New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024Transcript: New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC BiblioShare - Tech Forum 2024
 
Install Stable Diffusion in windows machine
Install Stable Diffusion in windows machineInstall Stable Diffusion in windows machine
Install Stable Diffusion in windows machine
 
Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024
 
Scanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsScanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL Certs
 
Unleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding ClubUnleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding Club
 

Generating Various and Consistent Behaviors in Simulations

  • 1. Generating Various and Consistent Behaviors in Simulations Benoît Lacroix 1,2, Philippe Mathieu 2 and Andras Kemeny 1 1 Renault, Technical Center for Simulation 2 LIFL, University of Lille March 26, 2009 PAAMS 2009
  • 2. Context and motivation  Renault / LIFL UMR CNRS collaboration  Context: traffic simulation in driving simulators  Evaluation of ergonomics, embedded systems, design…  Needs  Various and consistent behaviors for autonomous vehicles (cautious, aggressive…)  Usable by scenario designers  Idea  Driving psychologists classify drivers depending on their behavior (Saad, 1992)  Drivers use set of norms (based on Highway Code, informal rules…)  But they do not strictly follow these norms  Generic approach to address the issue  Behaviors description using norms  Generation engine managing the determinism  Monitoring Benoit Lacroix Renault, Technical Center for Simulation March 26, 2009 PAAMS 2009 2
  • 3. Normative description of behaviors  Normative systems (Noriega, 1997; Esteva et al., 2001; Vazquez-Salceda et al., 2005)  Organizational control in multi-agent based simulations  Improve agents coordination, communication…  In our case  Institution: parameters and associated definition domains  Norms: subsets of these parameters and domains  Behaviors: instantiations of these norms  For instance, in traffic  Parameters: maximal speed, safety time…  Institution: bounds of these parameters (max speed in [0,300] km/h)  Norms: cautious, aggressive drivers (max speed in [140,160] km/h)  Behavior: a cautious, an aggressive (max speed = 156 km/h) Benoit Lacroix Renault, Technical Center for Simulation March 26, 2009 PAAMS 2009 3
  • 4. Generation engine  Variety  Randomly select parameters from a norm  Behavioral variety within a norm  Allow violations: one or more parameters outside the limits  Consistency  Guaranteed when generation within norms limits  Mechanism to reject aberrant behaviors (quantification)  Reaction to violations at runtime Benoit Lacroix Renault, Technical Center for Simulation March 26, 2009 PAAMS 2009 4
  • 5. Monitoring  Emergence of new norms  Feedback to the users  Improve design and calibration  Calibration with real data  Learning norms from real data sets  Unsupervised learning  Kohonen Neural Networks  Description of the data space  Linear component analysis Benoit Lacroix Renault, Technical Center for Simulation March 26, 2009 PAAMS 2009 5
  • 6. Application  Application  Driving simulation software SCANeR™ II  Ergonomics, embedded systems, design, headlights…  Description  Agents’ decision model: perception – decision (finite state automata) – action (vehicle dynamic model)  Institution parameters = existing vehicles parameters of traffic model  Traffic managed by the existing model  Uses  Introduction of driving styles  Generation of the “ambient” traffic Benoit Lacroix Renault, Technical Center for Simulation March 26, 2009 PAAMS 2009 6
  • 7. Benoit Lacroix Renault, Technical Center for Simulation March 26, 2009 PAAMS 2009 7
  • 8. Experimental results  Highway database  11 km, 3000 veh/h  Normal, aggressive and cautious drivers  Speed distributions  More norms increase variety  Increased dynamicity  Lane repartition  Aggressive on left lane  Cautious on right lane Benoit Lacroix Renault, Technical Center for Simulation March 26, 2009 PAAMS 2009 8
  • 9. Conclusion  Easily create various behaviors  Manage the generation process  Guaranty the consistency of the behaviors  Allow violations if wished  Wide application range  Non-intrusive  Perspectives  Norms calibration with real data Benoit Lacroix Renault, Technical Center for Simulation March 26, 2009 PAAMS 2009 9
  • 10. Thank you for your attention Contact: benoit.lacroix@gmail.com Benoit Lacroix Renault, Technical Center for Simulation March 26, 2009 PAAMS 2009 10